As the core equipment of coal mining, shearer's healthy operation is the premise of safe and efficient mining of coal mine. Aiming at the problems of shearer health state evaluation in index construction, weight distribution, and evaluation result interpretation, a shearer health state evaluation model based on dynamic weight and fuzzy comprehensive evaluation is proposed. A two-stage evaluation index system of shearer is constructed by shearer structure and operation characteristics. The comprehensive weight (CW) with subjective and objective significance is obtained by analytic hierarchy process (AHP) and entropy weight (EW) method, then for the shortcomings of static weight distribution, dynamic weight coefficient is introduced to distribute the real-time weight of each index and update the model adaptively. Then the grey clustering method is used to evaluate the health states of the shearer's key components and the whole machine. In the case study of the MG400/930-WD shearer operating actual conditions, the method evaluation accuracy is 93.1%, compared with VW, EW, CW and BP method, the accuracy is increased by 9.2%, 6.7, 4.3%, and 3.1%. The example proves that this method can solve the problem of state evaluation of shearers and provide technical support for intelligent management and maintenance of mining equipment.